Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling

Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced. The International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, has been working on the development of a framework for defining and assessing uncertainties in the field of urban drainage modelling. A part of that work is the assessment and comparison of different techniques generally used in the uncertainty assessment of the parameters of water models. This paper compares a number of these techniques: the Generalized Likelihood Uncertainty Estimation (GLUE), the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA), an approach based on a multi-objective auto-calibration (a multialgorithm, genetically adaptive multi-objective method, AMALGAM) and a Bayesian approach based on a simplified Markov Chain Monte Carlo method (implemented in the software MICA). To allow a meaningful comparison among the different uncertainty techniques, common criteria have been set for the likelihood formulation, defining the number of simulations, and the measure of uncertainty bounds. Moreover, all the uncertainty techniques were implemented for the same case study, in which the same stormwater quantity and quality model was used alongside the same dataset. The comparison results for a well-posed rainfall/runoff model showed that the four methods provide similar probability distributions of model parameters, and model prediction intervals. For ill-posed water quality model the differences between the results were much wider; and the paper provides the specific advantages and disadvantages of each method. In relation to computational efficiency (i.e. number of iterations required to generate the probability distribution of parameters), it was found that SCEM-UA and AMALGAM produce results quicker than GLUE in terms of required number of simulations. However, GLUE requires the lowest modelling skills and is easy to implement. All non-Bayesian methods have problems with the way they accept behavioural parameter sets, e.g. GLUE, SCEM-UA and AMALGAM have subjective acceptance thresholds, while MICA has usually problem with its hypothesis on normality of residuals. It is concluded that modellers should select the method which is most suitable for the system they are modelling (e.g. complexity of the model’s structure including the number of parameters), their skill/knowledge level, the available information, and the purpose of their study.     

Lactobacillus casei strains isolated from cheese reduce biogenic amine accumulation in an experimental model

Tyramine and histamine are the biogenic amines (BAs) most commonly found in cheese, in which they appear as a result of the microbial enzymatic decarboxylation of tyrosine and histidine respectively. Given their toxic effects, their presence in high concentrations in foods should be avoided. In this work, samples of three cheeses (Zamorano, Cabrales and Emmental) with long ripening periods, and that often have high BA concentrations, were screened for the presence of BA-degrading lactic acid bacteria (LAB). Seventeen isolates were found that were able to degrade tyramine and histamine in broth culture. All 17 isolates were identified by 16S rRNA sequencing as belonging to Lactobacillus casei. They were typed by plasmid S1-PFGE and genomic macrorestriction-PFGE analysis. Two strains (L. casei 4a and 5b) associated with high degradation rates for both BAs were selected to test how this ability might affect histamine and tyramine accumulation in a Cabrales-like mini-cheese manufacturing model. The quantification of BAs and the monitoring of the strains' growth over ripening were undertaken by RP-HPLC and qPCR respectively. Both strains were found to reduce histamine and tyramine accumulation. These two strains might be suitable for use as adjunct cultures for reducing the presence of BAs in cheese.     

Synergistic effects between κ-carrageenan and locust bean gum on physicochemical properties of edible films made thereof

The development of mixed systems, formed by locust bean gum (LBG), and κ-carrageenan (κ-car) can offer new interesting applications such as the development of edible films with particular properties. κ-car/LBG blend films with different ratios were developed, and their effects on films’ physical properties were assessed. Thermogravimetric analysis (TGA), X-ray diffraction (XRD) patterns, dynamic mechanical analysis (DMA) and Fourier-transform infrared (FTIR) spectroscopy techniques were used to highlight the interactions between the two polysaccharides. The addition of κ-car to LBG improved the barrier properties of the films leading to a decrease of water vapor permeability (WVP). Improved values of elongation-at-break (EB) were registered when the ratio of κ-car/LBG was 80/20 or 40/60 (% w/w). Moreover, the κ-car/LBG blend films enhance the tensile strength (TS) compared to κ-car and LBG films. FTIR results suggested that hydrogen bonds interactions between κ-car and LBG have a great influence in films’ properties e.g. moisture content, WVP. Therefore, different κ-car/LBG ratios can be used to tailor edible films with enhanced barrier and mechanical properties.     

Determination of ochratoxin A in wines by capillary liquid chromatography with laser induced fluorescence detection using dispersive liquid-liquid microextraction

A method based on reverse phase capillary high performance liquid chromatography (capillary HPLC) coupled to laser-induced fluorescence detection (LIF) has been proposed for the determination of ochratoxin A (OTA) in wine samples. An anionic micellar medium was added to the mobile phase for increasing the fluorescence intensity and peak efficiency. Dispersive liquid-liquid microextraction (DLLME) has been used as a simple and efficient sample pretreatment method for the analysis of OTA in wines, being optimised by means of experimental design. The limit of detection was 5.5 ng L(-1) (3 × S/N) and recoveries for different wines ranged from 91.7 to 98.1%. The proposed methodology could be classified as a green analytical chemistry alternative, combining the low organic solvent volumes required in the DLLME with the reduced consumption of mobile phase in capillary HPLC. The use of LIF as detector provided an extremely sensitive method for the determination of OTA in wines.     

RNA fingerprinting analysis of Oenococcus oeni strains under wine conditions

Oenococcus oeni is a lactic acid bacterium of economic interest used in winemaking. This bacterium is the preferred species for malolactic fermentation (MLF) due its adaptability to the chemically harsh wine environment. MLF enhances the organoleptic properties and ensures deacidification of wines.     

Rheology and thermal behavior of polyamide reinforced with alumina whiskers

Alumina whiskers were melt‐mixed with polyamide 12 to obtain new composites with high performance properties and similar processability of neat polyamide. Three kinds of alumina whiskers were used to prepare composites (purified fibers, ribbon‐shaped fibers and silica‐coated fibers). The rheology, morphology and thermal behavior of composites were evaluated as function of the type of whisker and its amount in the samples. In terms of rheological properties, modulus and viscosity were enhanced as function of the amount of filler added. Good dispersion of alumina whiskers in PA12 and an optimal filler‐matrix interface were observed in morphological tests independently of the kind of fiber used. Studies on crystallization behavior indicated the nucleation action of whiskers, although the most important changes in crystalline state of PA12 were observed with ribbon‐shaped and silica‐coated fibers. Whiskers improved significantly the thermal stability of polyamide. But kinetics of degradation process studied using Coats‐Redfern method indicates that the best behavior wasobtained principally with ribbon‐shaped and silica‐coated whiskers. POLYM. COMPOS., 2012. © 2012 Society of Plastics Engineers     

A multi-residue method for the determination of 90 pesticides in matrices with a high water content by LC-MS/MS without clean-up

A method using QuEChERS extraction and LC-MS/MS in electrospray positive ionisation mode was developed and validated for the analysis of 90 pesticides in a high water content matrix (tomato) in a single chromatographic run. To assess the intra-laboratory reproducibility of the method, validation was conducted on four different days by two different analysts. The validation data was treated using a spreadsheet developed in-house, which sets the most appropriate model for linear fit by determining whether the residuals of the calibration curves are homocedastic or heterocedastic. A statistical test for the significance of regression was also carried out. Calibration was always matrix-matched and the curves were obtained over the range 0.0075-0.10 or 0.020-0.125 mg kg(-1). Identification of analytes was based on retention times and MRM ratios. Recoveries were assessed at four different levels for each analyte and were between 73 and 106%, with relative standard deviations under reproducibility conditions of <20%. The measurement uncertainties of the method for each pesticide analysed were below 50%. Previous validation of the same method, applied to papaya samples and satisfactory results obtained in various proficiency tests with different high water content matrices, demonstrated the applicability of the method to these classes of commodities, without clean-up. The validated method will be applied routinely in the pesticide residues monitoring programme that constitutes the National Residue and Contaminant Control Plan of Brazil.     

Technological Performance of the Enterocin A Producer <Emphasis Type="Italic">Enterococcus faecium</Emphasis> MMRA as a Protective Adjunct Culture to Enhance Hygienic and Sensory Attributes of Traditional Fermented Milk ‘Rayeb’

Enterococcus faecium MMRA is an enterocin A producer isolated from ‘Rayeb’, a Tunisian fermented milk drink. In this work, safety aspects and its behaviour in raw milk were investigated to assess its suitability as a protective adjunct culture. E. faecium MMRA showed interesting features such as the absence of several virulence traits, susceptibility to vancomycin and other clinically relevant antibiotics, and lack of haemolytic activity. To evaluate its performance as an adjunct culture for Rayeb, changes in the overall composition of control (non-inoculated) and experimental Rayeb (inoculated with 1%, v/v, E. faecium MMRA) were determined throughout duplicate fermentations of raw milk using microbiological, chemical, HPLC and headspace GC-MS analyses. E. faecium MMRA could multiply in raw milk and produced enterocin A. Interestingly, a higher content of volatile compounds including ethanol, diacetyl and 2-propanol was observed in the presence of this bacteriocin producer. Furthermore, this strain was capable of inhibiting the growth of Listeria monocytogenes CECT 4032 in pasteurised milk, although total killing was not achieved. Further experiments confirmed the development of resistant variants to enterocin A. On similar challenge assays, L. monocytogenes CECT 5672 growth was halted by the presence of the enterocin producer, but viability was only slightly reduced during cold storage. According to our results, E. faecium MMRA meets the criteria for an autochthonous protective adjunct culture to enhance both the hygienic and the sensory attributes of Rayeb.